1 00:00:01,040 --> 00:00:04,080 Speaker 1: Welcome to the Tutor Dixon Podcast. Today, I have Seamus 2 00:00:04,120 --> 00:00:07,360 Speaker 1: Bruner with us. He is the director of research at 3 00:00:07,360 --> 00:00:13,240 Speaker 1: the Government Accountability Institute and author of Control of Garcs, 4 00:00:13,320 --> 00:00:17,480 Speaker 1: exposing the billionaire class, their secret deals, and the globalist 5 00:00:17,560 --> 00:00:19,800 Speaker 1: plot to dominate your life. 6 00:00:19,920 --> 00:00:21,520 Speaker 2: Welcome to the podcast. 7 00:00:21,840 --> 00:00:23,279 Speaker 3: Hey, Tudor, great to be with you. 8 00:00:24,000 --> 00:00:24,840 Speaker 2: Well, it's a lot. 9 00:00:24,920 --> 00:00:26,800 Speaker 1: There's a lot going on, and I know you've been 10 00:00:26,800 --> 00:00:28,760 Speaker 1: out there talking about all of it. I think a 11 00:00:28,800 --> 00:00:32,280 Speaker 1: lot of people are wondering what exactly is happening in Minnesota. 12 00:00:32,600 --> 00:00:35,800 Speaker 1: We've heard about this like mystery billion dollars that has 13 00:00:35,880 --> 00:00:40,120 Speaker 1: gone missing and seems to be taken by the Somalian 14 00:00:40,200 --> 00:00:44,639 Speaker 1: community in some way. Elhan Omar, the congresswoman out there, 15 00:00:44,720 --> 00:00:48,839 Speaker 1: has been like kind of nonchalant, like, well it got lost, 16 00:00:48,920 --> 00:00:52,800 Speaker 1: it's the FBI's fault. And Waltz, the governor, is just 17 00:00:52,880 --> 00:00:55,720 Speaker 1: like ho hum, things like this happen. 18 00:00:56,280 --> 00:01:00,200 Speaker 4: What is going on? Yeah, So it's a it's a 19 00:01:00,200 --> 00:01:04,080 Speaker 4: pretty shocking story. I mean, usually the EBT fraud, welfare 20 00:01:04,160 --> 00:01:07,520 Speaker 4: fraud is in the millions, tens of millions. This case 21 00:01:07,520 --> 00:01:11,160 Speaker 4: in Minnesota tops one billion dollars. 22 00:01:10,840 --> 00:01:13,400 Speaker 3: And that is obviously a huge amount of money. 23 00:01:14,200 --> 00:01:18,520 Speaker 4: We've been tracking EBT and welfare fraud really since before 24 00:01:18,560 --> 00:01:21,640 Speaker 4: twenty eighteen. We put out a report I work with 25 00:01:21,680 --> 00:01:24,319 Speaker 4: Peter Schweitzer. By the way, we follow the money. We 26 00:01:24,360 --> 00:01:28,160 Speaker 4: put out a report called eb Terrorism and it traced 27 00:01:28,240 --> 00:01:32,160 Speaker 4: all of this money that goes from welfare scams to terrorists. 28 00:01:32,200 --> 00:01:34,720 Speaker 4: Now that actually does appear to be part of what's 29 00:01:34,760 --> 00:01:36,679 Speaker 4: gone on in Minnesota this time. 30 00:01:36,800 --> 00:01:38,720 Speaker 1: Do you say all of this money like this is 31 00:01:38,760 --> 00:01:39,560 Speaker 1: a regular thing. 32 00:01:40,080 --> 00:01:41,280 Speaker 3: Oh, it happens all the time. 33 00:01:41,480 --> 00:01:45,000 Speaker 4: I mean, it's crazy the amount of fraud, especially, I 34 00:01:45,040 --> 00:01:48,160 Speaker 4: mean wasted abuse as well. And the thing about entitlements, 35 00:01:48,200 --> 00:01:51,520 Speaker 4: things like welfare, you know, we want, And the thing 36 00:01:51,560 --> 00:01:54,040 Speaker 4: that's so disgusting about welfare fraud is that it really 37 00:01:54,080 --> 00:01:57,520 Speaker 4: does take away from disadvantaged people who need it, you know, 38 00:01:57,600 --> 00:02:00,360 Speaker 4: single mothers and children and all of this stuff. And 39 00:02:00,440 --> 00:02:04,200 Speaker 4: these people in Minnesota, I almost said, Somalia, these people 40 00:02:04,240 --> 00:02:09,360 Speaker 4: in Minnesota. A billion dollars was taken from starving children. 41 00:02:09,440 --> 00:02:10,040 Speaker 3: It's awful. 42 00:02:10,240 --> 00:02:12,080 Speaker 4: And the people who took it are you know, driving 43 00:02:12,520 --> 00:02:17,079 Speaker 4: luxury cars, luxury watches, mansions. So it's really one of 44 00:02:17,080 --> 00:02:20,560 Speaker 4: the most grotesque frauds around. And then as I was 45 00:02:20,600 --> 00:02:24,160 Speaker 4: saying about the terrorism component the reports indicate. 46 00:02:24,200 --> 00:02:26,080 Speaker 3: I mean, even the New York Times, by the way. 47 00:02:26,160 --> 00:02:30,440 Speaker 4: Has reported on how egregious this particular EBT welfare fraud 48 00:02:30,639 --> 00:02:34,440 Speaker 4: was in Minnesota. And that's how you know it's really bad. 49 00:02:34,639 --> 00:02:36,799 Speaker 4: Some of this money was apparently making it to l 50 00:02:36,880 --> 00:02:40,400 Speaker 4: Shabab terror networks, and that tracks with what we found, 51 00:02:40,440 --> 00:02:42,720 Speaker 4: I mean, in our report that we put out in 52 00:02:42,760 --> 00:02:46,840 Speaker 4: twenty eighteen, we found that the Boston bombers were using 53 00:02:47,080 --> 00:02:50,799 Speaker 4: welfare money to enable their schemes. Even the nine to 54 00:02:50,840 --> 00:02:54,440 Speaker 4: eleven hijackers, they're all kind of, you know, taking advantage 55 00:02:54,440 --> 00:02:56,519 Speaker 4: of welfare and what you need to know about a 56 00:02:56,600 --> 00:02:59,160 Speaker 4: terror attack, I mean, it seems maybe sort of obvious 57 00:02:59,360 --> 00:03:02,560 Speaker 4: that doesn't cost very much money to perpetrate an attack 58 00:03:02,639 --> 00:03:05,519 Speaker 4: like the Boston bombing was a pressure cooker and some 59 00:03:05,800 --> 00:03:09,520 Speaker 4: scrap metal, less than one hundred dollars really, And so 60 00:03:09,600 --> 00:03:11,760 Speaker 4: when you're talking about billions of dollars and some of 61 00:03:11,800 --> 00:03:15,720 Speaker 4: that money flowing out of Minnesota, away from Minnesota taxpayers, 62 00:03:16,120 --> 00:03:20,239 Speaker 4: hungry children, et cetera, and going to terror networks overseas, 63 00:03:21,120 --> 00:03:22,760 Speaker 4: the full weight of the Justice. 64 00:03:22,520 --> 00:03:24,639 Speaker 3: Department needs to come crashing down on this. 65 00:03:24,919 --> 00:03:27,640 Speaker 4: And then you mentioned Tim Walls, and of course ilhan Omar, 66 00:03:28,400 --> 00:03:30,960 Speaker 4: this really does lead to Governor Wallas. He's the one 67 00:03:30,960 --> 00:03:34,080 Speaker 4: who basically he or his office swept it under the rug. 68 00:03:34,880 --> 00:03:38,000 Speaker 4: And as The New York Times reported, he was trying 69 00:03:38,000 --> 00:03:41,760 Speaker 4: to protect a key voting block. And so that's the 70 00:03:41,800 --> 00:03:46,560 Speaker 4: thing here that's really so insidious is that these migrants 71 00:03:46,600 --> 00:03:49,560 Speaker 4: are voters for people like Tim Walls ilhan Omar, and 72 00:03:49,560 --> 00:03:51,840 Speaker 4: so they're willing to let them take food out of 73 00:03:51,880 --> 00:03:54,760 Speaker 4: the mouths of starving children. Some of it gets shipped 74 00:03:54,760 --> 00:03:57,520 Speaker 4: off to terrorism. I've not really seen a more egregious 75 00:03:57,560 --> 00:03:59,920 Speaker 4: case of welfare fraud here. 76 00:04:00,280 --> 00:04:02,200 Speaker 1: But when he talks about it, he's like, you can't 77 00:04:02,240 --> 00:04:05,040 Speaker 1: look into this because you're taking food out of the 78 00:04:05,040 --> 00:04:08,040 Speaker 1: mouths of babies, so you can't look into this. But 79 00:04:08,200 --> 00:04:11,040 Speaker 1: if you know that this has happened, and you know 80 00:04:11,160 --> 00:04:14,360 Speaker 1: that this money is being funneled in this way, and 81 00:04:14,360 --> 00:04:16,560 Speaker 1: in some of these there's like a weird connection with 82 00:04:16,600 --> 00:04:20,960 Speaker 1: elhan Omar, like she was with one of the organizers 83 00:04:21,000 --> 00:04:23,880 Speaker 1: of all of this Rea fundraiser or something. 84 00:04:23,720 --> 00:04:26,320 Speaker 2: Like she's she knows these people. 85 00:04:26,560 --> 00:04:29,400 Speaker 1: And yet she smugly went out on national TV and 86 00:04:29,520 --> 00:04:32,480 Speaker 1: was honestly like, well you know, if the FBI had 87 00:04:32,600 --> 00:04:34,080 Speaker 1: let it happen, it's their fault. 88 00:04:34,200 --> 00:04:38,640 Speaker 2: I can't do anything about it. And that is scary 89 00:04:38,760 --> 00:04:41,360 Speaker 2: to me that no one is holding her accountable. 90 00:04:42,760 --> 00:04:43,920 Speaker 3: Yeah, exactly right. 91 00:04:43,920 --> 00:04:46,680 Speaker 4: And the New York Times reported again, and you know, 92 00:04:46,680 --> 00:04:49,520 Speaker 4: I don't cite the Hereork Times because they're particularly trustworthy, 93 00:04:49,560 --> 00:04:53,360 Speaker 4: but the admission against their interest here is so striking. 94 00:04:53,720 --> 00:04:58,000 Speaker 4: They reported that in Somalia, there is a culture where 95 00:04:58,200 --> 00:05:01,040 Speaker 4: will Illjan and Omar comes from and the fraudsters, there 96 00:05:01,080 --> 00:05:04,039 Speaker 4: is a culture of corruption much more. It's much more 97 00:05:04,080 --> 00:05:07,000 Speaker 4: common over there than it is here. It's just kind 98 00:05:07,040 --> 00:05:10,080 Speaker 4: of like normal for you know, stealing and drifting off 99 00:05:10,120 --> 00:05:13,960 Speaker 4: of the government and getting coroni and corrupt contracts like 100 00:05:14,040 --> 00:05:16,960 Speaker 4: happened in Minnesota. And so for them to report that 101 00:05:17,120 --> 00:05:19,160 Speaker 4: is you know, that's not normal for the New York 102 00:05:19,200 --> 00:05:21,400 Speaker 4: Times to do that. And what you see time and again, 103 00:05:21,440 --> 00:05:23,200 Speaker 4: I mean there's all these viral clips right now on 104 00:05:23,279 --> 00:05:27,120 Speaker 4: social media, various Somalies from Minnesota. And of course not 105 00:05:27,200 --> 00:05:29,960 Speaker 4: all Somalians are bad, but you see these viral clips. 106 00:05:29,960 --> 00:05:32,039 Speaker 4: I mean, there was a rap video that just went 107 00:05:32,120 --> 00:05:35,640 Speaker 4: viral from a Smali rapper in Minnesota. There's other clips 108 00:05:35,680 --> 00:05:38,080 Speaker 4: where the guys saying, yeah, what's the big deal. I mean, 109 00:05:38,120 --> 00:05:40,159 Speaker 4: you know, fraud happens all the time. We're talking a 110 00:05:40,200 --> 00:05:44,640 Speaker 4: billion dollars. So for Tim Walls to say that it's actually, 111 00:05:44,800 --> 00:05:47,600 Speaker 4: you know, to project that it's not this key voting 112 00:05:47,640 --> 00:05:50,920 Speaker 4: block of his that was guilty. But instead, you know, 113 00:05:50,960 --> 00:05:54,000 Speaker 4: people who want to cut the programs, it's it's just 114 00:05:54,040 --> 00:05:56,520 Speaker 4: a little too rich, and this was. 115 00:05:56,600 --> 00:05:59,080 Speaker 2: I mean, this is clearly taxpayer money. 116 00:05:59,120 --> 00:06:03,720 Speaker 1: This is coming directly out of the welfare program, right, 117 00:06:03,720 --> 00:06:06,040 Speaker 1: But this is money that's going to I mean, it's 118 00:06:06,080 --> 00:06:09,080 Speaker 1: also money going to these organizations that are saying they're 119 00:06:09,160 --> 00:06:14,600 Speaker 1: managing how young people like children, single moms, children are 120 00:06:14,600 --> 00:06:17,240 Speaker 1: getting this food. So how do they how do they 121 00:06:17,279 --> 00:06:19,520 Speaker 1: do it? I mean, how do they funnel it through there? 122 00:06:21,240 --> 00:06:22,400 Speaker 3: It's it's it's shocking. 123 00:06:22,440 --> 00:06:25,240 Speaker 4: I mean, how how inept our government is, whether by 124 00:06:25,320 --> 00:06:29,160 Speaker 4: design or just you know, by nature, or whether it's 125 00:06:29,200 --> 00:06:32,919 Speaker 4: intentionally they're looking the other way. But uh, the amount 126 00:06:32,960 --> 00:06:35,200 Speaker 4: of work we've done in the last year looking into 127 00:06:35,279 --> 00:06:37,680 Speaker 4: like the stuff dozes looking at whether it's the EPA 128 00:06:38,279 --> 00:06:40,240 Speaker 4: or we just had a report come out on the 129 00:06:40,320 --> 00:06:44,720 Speaker 4: Small Business Administration has this DEI program. Uh, the rules 130 00:06:45,200 --> 00:06:47,280 Speaker 4: and and and just like what you have to say 131 00:06:47,360 --> 00:06:51,239 Speaker 4: to get a huge check from the government, it's it's crazy. 132 00:06:51,279 --> 00:06:54,000 Speaker 3: So there's really no oversight. There's really no accountability. 133 00:06:54,279 --> 00:06:58,200 Speaker 4: Once Congress, whether at the federal or state level, appropriates 134 00:06:58,240 --> 00:07:01,760 Speaker 4: money to a particular program, say they want to fund 135 00:07:01,600 --> 00:07:05,520 Speaker 4: the Child and Childless Hunger Initiative or they want to 136 00:07:05,560 --> 00:07:08,320 Speaker 4: fund some small business DEI program. Once that money has 137 00:07:08,360 --> 00:07:11,880 Speaker 4: been appropriated to the cause, the people who dole it out. 138 00:07:12,400 --> 00:07:14,360 Speaker 4: We just put out a report a five hundred and 139 00:07:14,360 --> 00:07:18,360 Speaker 4: fifty million dollars grant. They were paying the contracting grant 140 00:07:18,360 --> 00:07:21,600 Speaker 4: officials in the government over a million dollars in bribes 141 00:07:21,920 --> 00:07:25,040 Speaker 4: and there was no oversight, no accountability. We really wouldn't 142 00:07:25,040 --> 00:07:28,400 Speaker 4: know about it except for the Small Business Administration has 143 00:07:28,440 --> 00:07:32,280 Speaker 4: really taken seriously looking at all this and DOGE, I mean, 144 00:07:32,320 --> 00:07:35,840 Speaker 4: the elements that still remain are still exposing every day 145 00:07:36,080 --> 00:07:39,960 Speaker 4: new contracts and everyone more shocking than the last you. 146 00:07:39,920 --> 00:07:42,600 Speaker 1: Said, the elements that still remain of DOGE. Is that 147 00:07:42,680 --> 00:07:46,200 Speaker 1: a concern to you that there is not an actual 148 00:07:46,320 --> 00:07:49,040 Speaker 1: department that is I mean, there should be departments looking 149 00:07:49,040 --> 00:07:51,679 Speaker 1: at waste, broad and abuse, but this was a different level. 150 00:07:51,960 --> 00:07:55,040 Speaker 1: Is it a concern to you that those people are 151 00:07:55,040 --> 00:07:55,960 Speaker 1: not there to go to. 152 00:07:58,000 --> 00:07:59,040 Speaker 3: Yeah, it's I mean it was. 153 00:07:59,240 --> 00:08:01,880 Speaker 4: I think everybody's a little disappointed with how Doves sort 154 00:08:01,880 --> 00:08:05,800 Speaker 4: of fizzled out. We knew even before there was a 155 00:08:05,880 --> 00:08:10,040 Speaker 4: doge that reining in the spending from the Biden administration. 156 00:08:10,120 --> 00:08:12,240 Speaker 4: I mean, I don't know that people realize exactly how 157 00:08:12,320 --> 00:08:14,040 Speaker 4: much Joe Biden unleashed. 158 00:08:14,040 --> 00:08:16,040 Speaker 3: At first, it was his COVID Bill that was over 159 00:08:16,080 --> 00:08:16,600 Speaker 3: a trillion. 160 00:08:16,960 --> 00:08:20,400 Speaker 4: Then he had the Immigrant or the Infrastructure in Jobs 161 00:08:20,440 --> 00:08:24,200 Speaker 4: Act that was another trillion and a half. And then 162 00:08:24,240 --> 00:08:28,200 Speaker 4: there was the notorious Inflation Reduction Act, which will I mean, 163 00:08:28,240 --> 00:08:31,040 Speaker 4: it's over a trillion basically now all told, I mean 164 00:08:31,080 --> 00:08:34,320 Speaker 4: six trillion dollars in spending in just four years. I mean, 165 00:08:34,360 --> 00:08:38,480 Speaker 4: it's staggering. They really couldn't get it out fast enough. 166 00:08:38,760 --> 00:08:39,720 Speaker 2: The infrastructure. 167 00:08:39,760 --> 00:08:42,280 Speaker 1: I always joked that the infrastructure money and I don't 168 00:08:42,280 --> 00:08:44,720 Speaker 1: even know if this is a joke, but we Michigan 169 00:08:44,800 --> 00:08:47,560 Speaker 1: got some infrastructure money, and some of this was supposed 170 00:08:47,600 --> 00:08:50,720 Speaker 1: to make up for the fact that there were people 171 00:08:50,840 --> 00:08:53,679 Speaker 1: in the state that couldn't get online during the pandemic, 172 00:08:53,720 --> 00:08:56,280 Speaker 1: and we don't want that to ever be the case again. Right, 173 00:08:56,320 --> 00:08:58,960 Speaker 1: So we've got to make sure that there is internet 174 00:08:59,000 --> 00:09:02,520 Speaker 1: access across the entire state. And this is like, you know, 175 00:09:02,559 --> 00:09:05,120 Speaker 1: there's areas of Detroit where they weren't being able to 176 00:09:05,120 --> 00:09:07,000 Speaker 1: get on the internet. There were areas in the Upper 177 00:09:07,000 --> 00:09:09,840 Speaker 1: Peninsula where they couldn't get on the internet. I at 178 00:09:09,840 --> 00:09:13,560 Speaker 1: my house great internet, always have had great Internet, not 179 00:09:13,600 --> 00:09:16,640 Speaker 1: a problem whatsoever. This money comes into the state and 180 00:09:16,679 --> 00:09:19,080 Speaker 1: the next thing I know, there's someone digging up my 181 00:09:19,080 --> 00:09:21,600 Speaker 1: front yard and I'm like, what are you doing. Oh, 182 00:09:21,640 --> 00:09:24,120 Speaker 1: we're putting fiber in We've got and I said, why 183 00:09:24,120 --> 00:09:27,480 Speaker 1: are you putting? Where is this coming from? Well, we've 184 00:09:27,520 --> 00:09:30,920 Speaker 1: got a contract. I said, where is who has the contract? 185 00:09:30,920 --> 00:09:33,400 Speaker 1: The city has the contract. Why does the city of 186 00:09:33,440 --> 00:09:36,200 Speaker 1: the contract? The state got this money, The state got 187 00:09:36,240 --> 00:09:39,120 Speaker 1: money to put to make sure that people who have 188 00:09:39,440 --> 00:09:43,360 Speaker 1: no internet access have the infrastructure to have internet access. 189 00:09:43,679 --> 00:09:48,079 Speaker 1: Suddenly Frontier comes in. They get a big contract of 190 00:09:48,200 --> 00:09:52,040 Speaker 1: state funds that were really federal funds that came to 191 00:09:52,120 --> 00:09:57,080 Speaker 1: the state to put internet and nobody's monitoring where it's going. 192 00:09:57,520 --> 00:10:00,720 Speaker 1: So me, who, I already have great access, I'm getting 193 00:10:00,800 --> 00:10:04,520 Speaker 1: fiber in my front yard from a company who's getting 194 00:10:04,559 --> 00:10:06,680 Speaker 1: a massive amount of money to do it, but they're 195 00:10:06,720 --> 00:10:09,280 Speaker 1: getting money. And then the guy who's digging in the 196 00:10:09,280 --> 00:10:11,040 Speaker 1: middle of my front yard, I'm like, do we have 197 00:10:11,120 --> 00:10:12,960 Speaker 1: to put this rate in the middle of my front yard? 198 00:10:13,000 --> 00:10:14,800 Speaker 1: Do we not have this box off to the side. 199 00:10:14,840 --> 00:10:16,800 Speaker 1: Why are we putting this box in the middle of 200 00:10:16,840 --> 00:10:19,160 Speaker 1: my front yard. That's a whole other issue. 201 00:10:19,200 --> 00:10:19,800 Speaker 2: We moved it. 202 00:10:20,040 --> 00:10:23,160 Speaker 1: But he comes to my yard and I said, well, 203 00:10:23,200 --> 00:10:25,800 Speaker 1: who do you work for. He's like, oh, I just 204 00:10:25,840 --> 00:10:28,560 Speaker 1: got the contract to dig the holes. So I just 205 00:10:28,600 --> 00:10:30,480 Speaker 1: have this map and this is where I'm supposed to 206 00:10:30,520 --> 00:10:33,040 Speaker 1: put these holes. Like this is a massive amount of 207 00:10:33,080 --> 00:10:37,240 Speaker 1: money that I'm not opposed to infrastructure, but we didn't 208 00:10:37,280 --> 00:10:37,720 Speaker 1: need this. 209 00:10:38,240 --> 00:10:40,880 Speaker 2: It's like a lobbyist dream. 210 00:10:42,520 --> 00:10:47,120 Speaker 4: It totally was so yeah, IJA the Infrastructure and Jobs Act, 211 00:10:48,120 --> 00:10:51,840 Speaker 4: Investment in Infrastructure and Jobs Act, that was perhaps one 212 00:10:51,880 --> 00:10:54,440 Speaker 4: of the most ingregients. I think the real the worst 213 00:10:54,640 --> 00:10:57,160 Speaker 4: was because there were so much There was fifty billion 214 00:10:57,200 --> 00:10:59,160 Speaker 4: dollars or something, and they definitely didn't spend all of 215 00:10:59,200 --> 00:11:02,640 Speaker 4: that on on putting in high speed internet all over 216 00:11:02,679 --> 00:11:05,120 Speaker 4: the country. Apparently they just tore up your yard because 217 00:11:05,120 --> 00:11:08,000 Speaker 4: there are plenty of people who still don't have internet. 218 00:11:08,080 --> 00:11:08,800 Speaker 4: But it was. 219 00:11:09,040 --> 00:11:11,320 Speaker 2: I mean, the people that need actually need it. 220 00:11:12,520 --> 00:11:16,040 Speaker 3: Right, And it was a huge handout to blue states. 221 00:11:16,080 --> 00:11:17,800 Speaker 4: I mean, we compared the amount of money that the 222 00:11:17,840 --> 00:11:21,120 Speaker 4: federal government gave to the states to spend, and it 223 00:11:21,120 --> 00:11:24,200 Speaker 4: happened to in a lot of swing states suspiciously. But 224 00:11:24,320 --> 00:11:28,520 Speaker 4: in any case, the Inflation Reduction Act was even worse, 225 00:11:28,600 --> 00:11:31,240 Speaker 4: I would say than that, because at least somebody was 226 00:11:31,280 --> 00:11:33,120 Speaker 4: doing something. I mean, it was bad work. I mean, 227 00:11:33,120 --> 00:11:34,800 Speaker 4: it's so canesy and like we'll pay people to day 228 00:11:34,800 --> 00:11:37,439 Speaker 4: calls and then we'll pay them to fill them back in. 229 00:11:37,800 --> 00:11:42,600 Speaker 4: But the Inflation Reduction Act, I mean, we found over 230 00:11:42,640 --> 00:11:45,199 Speaker 4: one hundred billions first of all one hundred billion that 231 00:11:45,240 --> 00:11:48,959 Speaker 4: had flowed out of the Biden administration after President Trump 232 00:11:49,080 --> 00:11:52,120 Speaker 4: was elected in November twenty twenty four, but before he 233 00:11:52,200 --> 00:11:55,840 Speaker 4: was inaugurated, So in a ninety day span, over one 234 00:11:55,920 --> 00:11:57,160 Speaker 4: hundred billion dollars. 235 00:11:57,200 --> 00:11:59,640 Speaker 3: It was called gold bars off the Titanic. 236 00:11:59,640 --> 00:12:02,840 Speaker 4: I don't know if you saw that story involving EPA, 237 00:12:02,920 --> 00:12:07,319 Speaker 4: but also the Energy Department, the Agriculture Department for all 238 00:12:07,360 --> 00:12:09,960 Speaker 4: these programs that were just brand new, the Rural Access 239 00:12:10,000 --> 00:12:14,120 Speaker 4: to Internet or Rural Access to Energy program and it's. 240 00:12:13,920 --> 00:12:15,520 Speaker 3: Like shooting fish in a barrel. I mean, we've got 241 00:12:15,520 --> 00:12:16,199 Speaker 3: these spreadsheets. 242 00:12:16,240 --> 00:12:19,760 Speaker 4: The database we've built is thousands and thousands of rows 243 00:12:20,080 --> 00:12:23,880 Speaker 4: long with entities like ACBLLC and things that had been 244 00:12:23,920 --> 00:12:26,760 Speaker 4: set up just ten days before they got the money, 245 00:12:26,960 --> 00:12:27,520 Speaker 4: and something that. 246 00:12:27,640 --> 00:12:32,079 Speaker 1: Was there, something where that what Stacy Abrams didn't she 247 00:12:32,120 --> 00:12:34,360 Speaker 1: get a bunch of money like twenty million dollars to 248 00:12:34,400 --> 00:12:35,440 Speaker 1: spend in a half an hour. 249 00:12:36,320 --> 00:12:39,280 Speaker 4: It was it was two billion to power forward communities. 250 00:12:39,360 --> 00:12:41,840 Speaker 4: That yeah, it was two billion to a entity that 251 00:12:41,880 --> 00:12:43,920 Speaker 4: had did not exist six months prior. 252 00:12:44,640 --> 00:12:47,319 Speaker 3: Totally a purpose the term is purpose built. 253 00:12:47,320 --> 00:12:50,840 Speaker 4: If you look at a purpose built company for a 254 00:12:50,880 --> 00:12:53,320 Speaker 4: government grant is like it was just built to receive 255 00:12:53,440 --> 00:12:56,360 Speaker 4: money and they didn't even do anything with the money. 256 00:12:56,400 --> 00:12:59,960 Speaker 4: Nothing substantial anyway. And so my point with that, though, 257 00:13:00,160 --> 00:13:05,600 Speaker 4: is that Biden rushed through these three major spending bills, 258 00:13:05,640 --> 00:13:09,720 Speaker 4: the infrastructure one, the inflation one in the COVID one, 259 00:13:09,840 --> 00:13:13,920 Speaker 4: up to six trillion dollars possibly more when Congress passed those. 260 00:13:14,880 --> 00:13:17,000 Speaker 3: The way our constitution, our Supreme. 261 00:13:16,679 --> 00:13:20,319 Speaker 4: Court, our system is built is that when Congress passes 262 00:13:20,360 --> 00:13:23,160 Speaker 4: something and the president signs it, it's kind of sacrosanct. 263 00:13:23,200 --> 00:13:25,320 Speaker 3: It's not easy to undo it. 264 00:13:25,600 --> 00:13:28,160 Speaker 4: And so the real the fraud happened actually at the 265 00:13:28,160 --> 00:13:31,839 Speaker 4: congressional level and when Biden signed these bills. Because now 266 00:13:31,880 --> 00:13:34,599 Speaker 4: you bring into something like a Doge in a new administration, 267 00:13:34,920 --> 00:13:38,120 Speaker 4: you can't just cut the contracts. They were, you know, 268 00:13:38,280 --> 00:13:41,560 Speaker 4: lawfully you know, so it feels gross to say that, 269 00:13:41,600 --> 00:13:46,080 Speaker 4: but they were lawfully executed appropriation bills, and so Doge. 270 00:13:46,080 --> 00:13:47,679 Speaker 3: That's why it had such a problem. 271 00:13:47,720 --> 00:13:51,719 Speaker 4: As every single contract becomes a legal battle, it's almost infeasible. 272 00:13:51,800 --> 00:13:54,480 Speaker 1: Let's take a quick commercial break. We'll continue next on 273 00:13:54,480 --> 00:14:08,680 Speaker 1: a Tutor Dixon podcast. I think about just the whole 274 00:14:09,240 --> 00:14:12,800 Speaker 1: electric vehicle scam. I mean, this was something that was 275 00:14:13,360 --> 00:14:16,440 Speaker 1: legislated on a state level, also. 276 00:14:16,400 --> 00:14:17,760 Speaker 2: On a federal level. 277 00:14:17,960 --> 00:14:21,240 Speaker 1: I mean, you had states like California where Newsom was like, oh, 278 00:14:21,240 --> 00:14:24,040 Speaker 1: by twenty eight you'll never have another gas powered vehicle 279 00:14:24,080 --> 00:14:24,520 Speaker 1: in the state. 280 00:14:24,600 --> 00:14:25,400 Speaker 2: We won't allow it. 281 00:14:26,000 --> 00:14:30,800 Speaker 1: They forced the automotive industry to change their entire line. 282 00:14:30,960 --> 00:14:31,800 Speaker 1: So you think about it. 283 00:14:31,960 --> 00:14:33,480 Speaker 2: You've got the government forcing this. 284 00:14:33,720 --> 00:14:36,000 Speaker 1: But then the government's like, don't worry, We're going to 285 00:14:36,000 --> 00:14:38,080 Speaker 1: give people so much money to buy these cars. 286 00:14:38,160 --> 00:14:40,960 Speaker 2: It's going to suddenly go Suddenly, this is going to 287 00:14:41,040 --> 00:14:41,360 Speaker 2: catch on. 288 00:14:41,600 --> 00:14:44,640 Speaker 1: It reminds me of when they put me into labor 289 00:14:44,680 --> 00:14:46,520 Speaker 1: early and they said at night, we're going to take 290 00:14:46,560 --> 00:14:48,480 Speaker 1: off the potosin in your body's probably just going to 291 00:14:48,480 --> 00:14:50,880 Speaker 1: go into labor and guess what, it didn't because that's 292 00:14:50,920 --> 00:14:53,000 Speaker 1: not how it worked, and that the same thing with 293 00:14:53,040 --> 00:14:56,440 Speaker 1: the automotive industry. People didn't just suddenly go oh, you 294 00:14:56,440 --> 00:14:58,680 Speaker 1: know what, yes, I want electric vehicles. 295 00:14:58,920 --> 00:14:59,880 Speaker 2: They didn't sell. 296 00:15:00,280 --> 00:15:03,640 Speaker 1: The minute Biden was out of office, Trump was like, Okay, 297 00:15:03,680 --> 00:15:06,800 Speaker 1: we're done with paying people to buy cars. And then 298 00:15:06,880 --> 00:15:11,120 Speaker 1: suddenly the automotive industry, mysteriously, how funny, They're like, oh, 299 00:15:11,200 --> 00:15:13,040 Speaker 1: we're not going to get money from the government for 300 00:15:13,160 --> 00:15:15,400 Speaker 1: your cars. Then we're not actually going to make these 301 00:15:15,400 --> 00:15:18,600 Speaker 1: cars because we can't sell them. And now here I 302 00:15:18,640 --> 00:15:20,920 Speaker 1: am in the state of Michigan. I talked to a 303 00:15:20,960 --> 00:15:23,920 Speaker 1: guy at Dollar General the other day that I used 304 00:15:23,920 --> 00:15:26,240 Speaker 1: to work with at the foundry, and I said, how's 305 00:15:26,280 --> 00:15:28,560 Speaker 1: it going, And he goes, well, I'm a Tier one 306 00:15:28,600 --> 00:15:31,640 Speaker 1: supplier to the automotive industry and they just shut down 307 00:15:31,640 --> 00:15:32,720 Speaker 1: all the EV lines. 308 00:15:32,960 --> 00:15:33,960 Speaker 2: It's all a scam. 309 00:15:34,800 --> 00:15:37,640 Speaker 4: Oh and it has real world consequences like that. I 310 00:15:38,280 --> 00:15:40,200 Speaker 4: write about it a lot in the book Control of Arts. 311 00:15:40,240 --> 00:15:42,480 Speaker 4: I mean there's a whole chapter because this isn't just 312 00:15:42,840 --> 00:15:45,760 Speaker 4: bureaucratic incompetence. And that was the whole point of the book, 313 00:15:45,840 --> 00:15:49,640 Speaker 4: is that there is this class above the political class 314 00:15:50,240 --> 00:15:53,280 Speaker 4: who was actually pushing for these massive spending bills. And 315 00:15:53,320 --> 00:15:56,480 Speaker 4: it's not just political operatives like Stacy Abrams. And we 316 00:15:56,520 --> 00:15:59,840 Speaker 4: can talk actually about how the left uses your tax 317 00:16:00,320 --> 00:16:03,280 Speaker 4: as a force multiplier for their own agenda, whether it's 318 00:16:03,360 --> 00:16:07,360 Speaker 4: open borders, resettling migrants, or get out the vote. We 319 00:16:07,480 --> 00:16:09,680 Speaker 4: have that rioting report. We could talk about that, but 320 00:16:10,480 --> 00:16:12,840 Speaker 4: it just for example. In the in the War on 321 00:16:12,960 --> 00:16:15,720 Speaker 4: Farmers chapter, I talk about how, why, how and why 322 00:16:15,760 --> 00:16:18,440 Speaker 4: Bill Gates is trying to buy up all this farmland 323 00:16:18,520 --> 00:16:22,440 Speaker 4: and put you know, generation five, six seven, generation owned 324 00:16:22,480 --> 00:16:24,760 Speaker 4: farms out of business. 325 00:16:24,640 --> 00:16:26,640 Speaker 3: And why he is not a coincidence. 326 00:16:26,640 --> 00:16:30,320 Speaker 4: He's simultaneously invested in all of the largest alternative so 327 00:16:30,400 --> 00:16:33,600 Speaker 4: called alternative protein I call it fake meat or lab 328 00:16:33,640 --> 00:16:37,160 Speaker 4: grown meat companies like Beyond, you know, Beyond Burgers, Impossibles, 329 00:16:37,160 --> 00:16:39,880 Speaker 4: another thing that's not going to catch on exactly. So 330 00:16:39,920 --> 00:16:42,680 Speaker 4: they pumped all this money into a bunch of taxpayer money. 331 00:16:42,720 --> 00:16:46,120 Speaker 4: They use threats of like methane. You know, Alexandria Costio 332 00:16:46,160 --> 00:16:48,320 Speaker 4: Cortez did not just invent one day in her mind 333 00:16:48,360 --> 00:16:51,200 Speaker 4: that cal flatulence is a threat to the environment that 334 00:16:51,280 --> 00:16:53,560 Speaker 4: comes from a you know, a bill I will int 335 00:16:53,560 --> 00:16:57,040 Speaker 4: the Gates Foundation or you know, similar white paper saying 336 00:16:57,080 --> 00:16:59,640 Speaker 4: that it is so that they can target the farmers. 337 00:16:59,640 --> 00:17:02,560 Speaker 4: And so the real world consequences is ask any. 338 00:17:02,400 --> 00:17:04,640 Speaker 3: Farmer, it is harder and harder. I mean, they're going 339 00:17:04,640 --> 00:17:05,320 Speaker 3: out of business. 340 00:17:05,320 --> 00:17:09,080 Speaker 4: You can't really turn a profit because a the environmental regulations, 341 00:17:09,119 --> 00:17:13,000 Speaker 4: but then the subsidies. And at the same time, customers, consumers, 342 00:17:13,160 --> 00:17:15,679 Speaker 4: they don't want fake meat. So all of this money wasted, 343 00:17:15,680 --> 00:17:19,399 Speaker 4: people's lives wrecked to push a product that nobody wants. 344 00:17:19,920 --> 00:17:22,320 Speaker 1: It's because they started with I mean, part of the 345 00:17:22,359 --> 00:17:24,600 Speaker 1: problem there is they started with like, look, you can 346 00:17:24,640 --> 00:17:29,159 Speaker 1: eat crickets and cockroaches and they're just as good. It's like, no, 347 00:17:29,320 --> 00:17:31,959 Speaker 1: thank you, and we will never eat We'll never eat that. 348 00:17:32,560 --> 00:17:35,840 Speaker 1: So we have all this money that is going into 349 00:17:36,880 --> 00:17:39,159 Speaker 1: all of this other stuff. But you talked about getting 350 00:17:39,200 --> 00:17:42,240 Speaker 1: out the vote, and you talked about riot inc and 351 00:17:42,440 --> 00:17:45,440 Speaker 1: you talk about all of this. I want to get 352 00:17:45,480 --> 00:17:49,080 Speaker 1: into a little bit about how they have controlled this 353 00:17:49,320 --> 00:17:54,400 Speaker 1: narrative about Israel and Palestine and used that to get 354 00:17:54,400 --> 00:17:56,640 Speaker 1: people to come out and vote. And I say that 355 00:17:57,119 --> 00:18:02,639 Speaker 1: because we've just seen this horrific attack on Bondai Beach, 356 00:18:02,800 --> 00:18:07,520 Speaker 1: and we saw that, we see this anti Semitism growing 357 00:18:07,560 --> 00:18:10,520 Speaker 1: across the country. And I do believe that there are 358 00:18:10,640 --> 00:18:12,960 Speaker 1: useful idiots that are like, oh, this is a message 359 00:18:12,960 --> 00:18:14,800 Speaker 1: that will get people to vote, and they don't even 360 00:18:14,840 --> 00:18:18,040 Speaker 1: realize that there's a bigger message, a more dangerous message 361 00:18:18,040 --> 00:18:20,879 Speaker 1: going out there. And I think we are seeing it 362 00:18:22,160 --> 00:18:25,800 Speaker 1: fivefold across the globe right now because of what's happening 363 00:18:26,040 --> 00:18:30,160 Speaker 1: with American politics and the manipulation of money. So tell 364 00:18:30,240 --> 00:18:31,480 Speaker 1: us a little bit about rioting. 365 00:18:32,880 --> 00:18:36,520 Speaker 4: Yeah, So, at the White House roughly a month ago, 366 00:18:36,520 --> 00:18:40,359 Speaker 4: President Trump invited me and several other journalists like Andy 367 00:18:40,480 --> 00:18:43,240 Speaker 4: No Julio Rosas the people who are really on the 368 00:18:43,240 --> 00:18:47,280 Speaker 4: ground dealing with the Antifa threat. And the point I 369 00:18:47,359 --> 00:18:50,560 Speaker 4: brought was that none of this is organic. There's a 370 00:18:50,560 --> 00:18:54,160 Speaker 4: lot of domestic money, even your own taxpayer money, going 371 00:18:54,200 --> 00:18:58,200 Speaker 4: into what we called riot inc, the protest industrial complex. 372 00:18:58,440 --> 00:19:01,040 Speaker 4: And you've seen it all year long, these anti ice 373 00:19:01,800 --> 00:19:04,000 Speaker 4: riots out in Portland, Seattle. 374 00:19:05,200 --> 00:19:06,119 Speaker 3: You know, in Chicago. 375 00:19:06,920 --> 00:19:09,320 Speaker 4: And so you know, we've because we had looked into 376 00:19:09,320 --> 00:19:12,600 Speaker 4: how much money these big left wing NGOs get Soros, 377 00:19:13,080 --> 00:19:15,240 Speaker 4: the Arabella funding network tides. 378 00:19:15,880 --> 00:19:18,040 Speaker 3: Nevill Roy Singham was one of the names that we 379 00:19:18,119 --> 00:19:19,800 Speaker 3: brought up at the White House. 380 00:19:21,080 --> 00:19:24,240 Speaker 4: There's a huge foreign element here, like with the CCP 381 00:19:24,400 --> 00:19:25,840 Speaker 4: alignment with nevill Roy Singham. 382 00:19:25,880 --> 00:19:26,800 Speaker 3: He lives in China. 383 00:19:27,160 --> 00:19:31,399 Speaker 4: He's doing the bidding, we believe, of the CCP and 384 00:19:31,480 --> 00:19:33,960 Speaker 4: sowing these divisions and all of this chaos. He was 385 00:19:34,000 --> 00:19:38,520 Speaker 4: a big funder an organizer of the pro hamas rallies 386 00:19:38,560 --> 00:19:41,199 Speaker 4: in New York City after October seventh. He's also a 387 00:19:41,200 --> 00:19:44,119 Speaker 4: big funder of all of these anti Ice riots. He 388 00:19:44,280 --> 00:19:47,480 Speaker 4: was a huge funder of the BLM Rights of twenty twenty. 389 00:19:47,600 --> 00:19:50,520 Speaker 4: And so he is sowing this division in this chaos 390 00:19:50,640 --> 00:19:55,119 Speaker 4: among many other forces, these radical left nngos, Soros Arabella types, 391 00:19:55,840 --> 00:19:57,720 Speaker 4: And so you know, we dug into that. We showed 392 00:19:57,720 --> 00:20:01,159 Speaker 4: that to President Trump. He was shocked our research to 393 00:20:01,400 --> 00:20:04,879 Speaker 4: the appropriate agencies. But we wanted to diggle even a 394 00:20:04,920 --> 00:20:08,960 Speaker 4: little further because we were wondering, why do they want 395 00:20:09,000 --> 00:20:13,520 Speaker 4: to why are these riots so anti Ice? And what 396 00:20:13,560 --> 00:20:17,040 Speaker 4: we found is that the exact same big NGOs that 397 00:20:17,119 --> 00:20:19,359 Speaker 4: get your tax dollars, by the way, hundreds of millions 398 00:20:19,400 --> 00:20:22,800 Speaker 4: of them. They are the same ones who funded the 399 00:20:22,800 --> 00:20:24,920 Speaker 4: Biden border crisis. They are the same ones who brought 400 00:20:24,920 --> 00:20:27,879 Speaker 4: in ten million people and resettled them all throughout the country. 401 00:20:27,880 --> 00:20:30,360 Speaker 4: And we said, you know, that led to another question, Well, 402 00:20:30,680 --> 00:20:32,320 Speaker 4: you know, do they just I mean, why do they 403 00:20:32,359 --> 00:20:36,720 Speaker 4: want to eliminate borders? Are they just total globalists? That's true, 404 00:20:37,000 --> 00:20:40,040 Speaker 4: but there's actually a commercial component here, and there's the 405 00:20:40,040 --> 00:20:42,199 Speaker 4: get out the vote component. So we found it's the 406 00:20:42,200 --> 00:20:45,080 Speaker 4: same players too. And Bill Gates was a huge funder 407 00:20:45,080 --> 00:20:48,240 Speaker 4: of Arabella over the past five years three hundred million. 408 00:20:48,880 --> 00:20:51,320 Speaker 4: You know, a lot of the other left wing tech 409 00:20:51,359 --> 00:20:55,479 Speaker 4: oligarchs were big funders of these tides Arabella. You know, 410 00:20:56,000 --> 00:21:00,920 Speaker 4: there's the Ford Foundation, et cetera, Rockefeller Foundation. They're also 411 00:21:01,000 --> 00:21:03,240 Speaker 4: invested in the get out the vote operation. And so 412 00:21:04,160 --> 00:21:06,760 Speaker 4: there's a direct line from the open border to the 413 00:21:06,800 --> 00:21:07,480 Speaker 4: ballot box. 414 00:21:07,520 --> 00:21:08,440 Speaker 3: I mean, whether they're. 415 00:21:08,280 --> 00:21:11,400 Speaker 4: Illegally getting people onto the voter rules or just wait, 416 00:21:11,400 --> 00:21:12,160 Speaker 4: it's a waiting game. 417 00:21:12,200 --> 00:21:13,280 Speaker 3: It's a time game. 418 00:21:13,320 --> 00:21:17,040 Speaker 4: I mean, within five years or less, they can become donors. 419 00:21:17,080 --> 00:21:19,680 Speaker 4: You know, people with green cards and permanent residence status, 420 00:21:19,880 --> 00:21:23,760 Speaker 4: can become donors, or eventually they can actually legally vote 421 00:21:23,760 --> 00:21:26,560 Speaker 4: if they're not getting on the roles illegally. And then 422 00:21:26,560 --> 00:21:29,120 Speaker 4: of course there's some precincts where they can actually legally vote. 423 00:21:29,119 --> 00:21:32,720 Speaker 4: Non citizens can vote in places like California, et cetera. 424 00:21:32,840 --> 00:21:36,240 Speaker 4: And then the final thing is apportionment. When you bring 425 00:21:36,280 --> 00:21:38,639 Speaker 4: ten million people in and you distribute them to various 426 00:21:38,640 --> 00:21:42,159 Speaker 4: places like California, that gives them a lot more you know, 427 00:21:42,480 --> 00:21:45,919 Speaker 4: a dozen maybe in California representatives that they shouldn't have, 428 00:21:46,080 --> 00:21:49,320 Speaker 4: or you know, more than five ten. You know, there's 429 00:21:49,359 --> 00:21:53,119 Speaker 4: not really it's not clear how many left wing progressive 430 00:21:53,560 --> 00:21:57,040 Speaker 4: congress people we have specifically because of the large influx 431 00:21:57,080 --> 00:22:00,520 Speaker 4: of migrants. But that's just another added benefit. So it's 432 00:22:00,560 --> 00:22:03,080 Speaker 4: commercial and it's also ideological. 433 00:22:03,440 --> 00:22:05,960 Speaker 1: Well, I'm glad that you brought up Nevill Roy Singham 434 00:22:06,080 --> 00:22:09,480 Speaker 1: at the White House because he is married to the 435 00:22:09,480 --> 00:22:13,280 Speaker 1: co founder of Code Pink, the co founder. The other 436 00:22:13,359 --> 00:22:17,160 Speaker 1: co founder is Medea Benjamin, and that is the person 437 00:22:17,280 --> 00:22:20,640 Speaker 1: who Marjorie Taylor Green has been posting that she's friends with, 438 00:22:20,880 --> 00:22:24,000 Speaker 1: which is very interesting to me because in twenty three 439 00:22:24,080 --> 00:22:27,640 Speaker 1: she posted a tweet that said you know, I'm out 440 00:22:27,680 --> 00:22:31,040 Speaker 1: here with Code Pink talking to them and they're anti war, 441 00:22:31,160 --> 00:22:33,960 Speaker 1: but they have as soon as they made this connection 442 00:22:34,119 --> 00:22:38,480 Speaker 1: with Singham, there has been some they've been very pro 443 00:22:38,560 --> 00:22:42,560 Speaker 1: hamas they've been out there pro Palestine and they've been 444 00:22:42,880 --> 00:22:45,919 Speaker 1: they've stopped Jewish people in the halls of Congress and 445 00:22:46,080 --> 00:22:48,280 Speaker 1: screamed from the river to the sea. I mean that 446 00:22:48,440 --> 00:22:51,719 Speaker 1: is a call for genocide. It's like literally looking at 447 00:22:51,720 --> 00:22:54,320 Speaker 1: someone and saying I wish you were dead. And they've 448 00:22:54,359 --> 00:22:56,560 Speaker 1: been doing this in the halls of Congress. I will 449 00:22:56,560 --> 00:23:00,560 Speaker 1: say those people should be tracked down on video and 450 00:23:00,680 --> 00:23:02,800 Speaker 1: they should be banned from the halls of Congress because 451 00:23:02,800 --> 00:23:05,760 Speaker 1: you should not be allowed to do that inside our 452 00:23:06,240 --> 00:23:09,520 Speaker 1: sacred buildings. But they are doing that, they're calling, they're 453 00:23:09,560 --> 00:23:12,760 Speaker 1: saying that to people's faces, essentially, I want you dead. 454 00:23:14,280 --> 00:23:18,960 Speaker 1: Has How has that connection, How does that connection to 455 00:23:19,200 --> 00:23:21,639 Speaker 1: a Roy Singham change an organization like that. 456 00:23:23,520 --> 00:23:24,240 Speaker 3: I mean it's huge. 457 00:23:24,280 --> 00:23:26,919 Speaker 4: I mean Nevill Roy Singham again, he's funding not just 458 00:23:27,000 --> 00:23:28,800 Speaker 4: I mean it's a major funder of Code Pink, but 459 00:23:28,880 --> 00:23:31,639 Speaker 4: his People's Forum. We put out a report that actually 460 00:23:31,680 --> 00:23:35,200 Speaker 4: got some big traction his People's Forum and in Nevill 461 00:23:35,280 --> 00:23:39,800 Speaker 4: Roy Singham's funding to Cuba and to the venture most Brigade. 462 00:23:39,800 --> 00:23:42,560 Speaker 4: I could list half a dozen Cuban entities that are 463 00:23:42,600 --> 00:23:47,800 Speaker 4: directly tied to Cuban intelligence, Communist intelligence, and this group 464 00:23:47,880 --> 00:23:51,880 Speaker 4: brought down over seven hundred American groups BLM activists, etc. 465 00:23:52,200 --> 00:23:57,000 Speaker 4: Down to Cuba to receive Marxist revolutionary training. The one 466 00:23:57,000 --> 00:23:59,520 Speaker 4: that put this on our radar was the Armed Queers 467 00:23:59,560 --> 00:24:01,800 Speaker 4: of Salt Lake City. This group kind of popped up 468 00:24:02,040 --> 00:24:06,120 Speaker 4: after the Charlie Kirk assassination. They you know, there's no 469 00:24:06,480 --> 00:24:09,400 Speaker 4: I'll be clear, there's no direct tie to Kirk's assassination, 470 00:24:09,760 --> 00:24:12,879 Speaker 4: but everybody noticed it and we were able to scrape 471 00:24:12,960 --> 00:24:16,119 Speaker 4: all of their social media get videos of this group 472 00:24:16,200 --> 00:24:20,160 Speaker 4: down in Cuba getting their Marxist revolutionary training. We got 473 00:24:20,160 --> 00:24:22,680 Speaker 4: their whole substack before they took it down, and they 474 00:24:22,680 --> 00:24:25,560 Speaker 4: were talking about their goal is to overthrow the United States. 475 00:24:25,760 --> 00:24:27,800 Speaker 4: These are the kind of groups that Nevill Roy Singham 476 00:24:27,880 --> 00:24:29,679 Speaker 4: backs and brings down to Cuba. 477 00:24:29,840 --> 00:24:32,000 Speaker 3: And a lot of people know that Cuba had this 478 00:24:32,119 --> 00:24:32,600 Speaker 3: tie to. 479 00:24:32,680 --> 00:24:35,959 Speaker 4: Russia, you know, during the Cold War, but that has 480 00:24:36,000 --> 00:24:39,320 Speaker 4: really kind of turned into more of a China connection. 481 00:24:39,480 --> 00:24:43,159 Speaker 4: China has really set up out posts in Cuba, ninety miles. 482 00:24:42,920 --> 00:24:44,280 Speaker 3: From our border. I'm down in Florida. 483 00:24:44,400 --> 00:24:46,800 Speaker 4: It doesn't give us a great comfort to know that 484 00:24:46,920 --> 00:24:50,920 Speaker 4: just ninety miles away you have this CCP Foothold training 485 00:24:51,320 --> 00:24:56,920 Speaker 4: American citizens how to become revolutionary Marxists. But that's just 486 00:24:57,040 --> 00:24:59,520 Speaker 4: one of the many things. Nevill Roy Singam also funds 487 00:24:59,520 --> 00:25:02,480 Speaker 4: a group called TURLA. It was the coalition for I 488 00:25:02,480 --> 00:25:05,960 Speaker 4: think it's humane immigrant rights in Los Angeles. They were, 489 00:25:06,359 --> 00:25:10,320 Speaker 4: you know, accused or Senator Hawley among others sent them 490 00:25:10,400 --> 00:25:13,000 Speaker 4: letters and they've been investigated for their role in the 491 00:25:13,119 --> 00:25:16,719 Speaker 4: violent anti ice riots out on the West coast. And 492 00:25:16,800 --> 00:25:20,439 Speaker 4: so like I mentioned the BLM stuff, the pro Hama 493 00:25:20,480 --> 00:25:25,240 Speaker 4: stuff after October seventh, and for Marjorie Taylor Green to 494 00:25:25,280 --> 00:25:28,480 Speaker 4: take one be in a photo to be friends with, 495 00:25:28,880 --> 00:25:30,520 Speaker 4: I mean, I guess it's worse to be friends with 496 00:25:30,680 --> 00:25:35,159 Speaker 4: and like the photos just a total unforced error in 497 00:25:35,200 --> 00:25:36,240 Speaker 4: a long line of them. 498 00:25:36,320 --> 00:25:39,040 Speaker 1: So well, that's I think that's the stunning thing. Like 499 00:25:39,080 --> 00:25:42,240 Speaker 1: I said, for me, as I watched this, I'm like, okay. 500 00:25:42,240 --> 00:25:45,119 Speaker 1: In twenty three she went outside, she gets a picture 501 00:25:45,160 --> 00:25:47,879 Speaker 1: with them, she posts it, she says she's anti war. 502 00:25:48,240 --> 00:25:50,720 Speaker 1: We know that's been her stance for a long time. 503 00:25:50,800 --> 00:25:54,040 Speaker 1: She wants no foreign wars, she doesn't want the United 504 00:25:54,080 --> 00:25:57,879 Speaker 1: States to be involved in anything, Okay, But then there's 505 00:25:57,920 --> 00:26:04,480 Speaker 1: this sudden switch in what seems to be her or 506 00:26:04,600 --> 00:26:08,560 Speaker 1: her allegiance to her constituents who voted for her because 507 00:26:08,560 --> 00:26:10,679 Speaker 1: they believed that she was a part of the Republican 508 00:26:10,720 --> 00:26:15,080 Speaker 1: Party and supported the policies of this administration, and she 509 00:26:15,320 --> 00:26:18,639 Speaker 1: suddenly completely shifted on that, and then she posts this like, 510 00:26:18,720 --> 00:26:21,960 Speaker 1: I'm America first. I'm fully against funding foreign wars and 511 00:26:22,000 --> 00:26:25,480 Speaker 1: support peace because that's good for everyone, especially the most 512 00:26:25,560 --> 00:26:29,359 Speaker 1: innocent people children. I have enjoyed a friendship with Medea 513 00:26:29,560 --> 00:26:32,920 Speaker 1: for a few years now, even though politics says that's 514 00:26:32,920 --> 00:26:33,480 Speaker 1: not allowed. 515 00:26:33,720 --> 00:26:34,600 Speaker 2: Whoa wait a. 516 00:26:34,560 --> 00:26:39,520 Speaker 1: Minute, Politics doesn't say that's not allowed. I mean, your 517 00:26:39,680 --> 00:26:42,520 Speaker 1: values should say that's not allowed. This is somebody who 518 00:26:42,600 --> 00:26:46,920 Speaker 1: is pushing CCP propaganda in the United States that has 519 00:26:47,240 --> 00:26:50,440 Speaker 1: had people in the halls of Congress telling Jewish people 520 00:26:50,440 --> 00:26:53,280 Speaker 1: they wish they were dead. I mean, this is not 521 00:26:53,440 --> 00:26:57,399 Speaker 1: protection of young people. Is she misguided or has this 522 00:26:57,600 --> 00:26:59,920 Speaker 1: total switch been because of this? Can? 523 00:27:00,280 --> 00:27:02,760 Speaker 2: I mean that is that is the These are the. 524 00:27:02,760 --> 00:27:05,239 Speaker 1: Questions that I have about what is going on with 525 00:27:05,359 --> 00:27:08,080 Speaker 1: Marjorie Taylor Green. But as you've pointed out, Code Pink 526 00:27:08,640 --> 00:27:11,720 Speaker 1: is out there doing these things and they are dangerous 527 00:27:11,720 --> 00:27:12,480 Speaker 1: for our country. 528 00:27:14,359 --> 00:27:16,680 Speaker 4: Yeah, I mean, I've got I've got opinions on why 529 00:27:16,920 --> 00:27:18,919 Speaker 4: Marjorie Taylor Green has done this. I mean, you know, 530 00:27:19,000 --> 00:27:22,200 Speaker 4: there's been reporting and she got snubbed by the Trump administration, 531 00:27:22,320 --> 00:27:26,080 Speaker 4: didn't get an appointment. I don't really know why she 532 00:27:26,119 --> 00:27:27,639 Speaker 4: did this. I don't I don't know. I don't have 533 00:27:27,680 --> 00:27:29,760 Speaker 4: any evidence that it's like a financial reason. I think 534 00:27:29,800 --> 00:27:31,960 Speaker 4: it seems to sort of track that she realized that 535 00:27:32,000 --> 00:27:34,240 Speaker 4: she'd reached kind of the ceiling. You're not supposed to 536 00:27:34,280 --> 00:27:36,679 Speaker 4: give up though. I mean, you're I'm exactly right to 537 00:27:36,800 --> 00:27:40,160 Speaker 4: mention her constituents. And so what this kind of looks 538 00:27:40,200 --> 00:27:42,399 Speaker 4: like is just really trying to stick it to Donald Trump. 539 00:27:42,640 --> 00:27:43,600 Speaker 3: I mean, you saw the video. 540 00:27:43,640 --> 00:27:45,720 Speaker 4: I may may a lot of people saw the video 541 00:27:45,720 --> 00:27:48,560 Speaker 4: went viral of the Code Pink activists getting up in 542 00:27:48,600 --> 00:27:50,359 Speaker 4: Donald Trump's face when he was trying to have dinner 543 00:27:50,400 --> 00:27:53,200 Speaker 4: at a restaurant. Seemed like a total national security thread. 544 00:27:53,200 --> 00:27:55,639 Speaker 4: I'm not sure how they were, you know, allowed to 545 00:27:55,720 --> 00:27:58,680 Speaker 4: do that, but they were swiftly kind of ushered out. 546 00:27:59,480 --> 00:28:03,160 Speaker 4: In any case, it's an obvious slap in the face 547 00:28:03,200 --> 00:28:05,320 Speaker 4: to President Trump to align with the group that is 548 00:28:05,359 --> 00:28:07,880 Speaker 4: so anti Trump. And and she's been doing stuff like this 549 00:28:08,600 --> 00:28:11,200 Speaker 4: for a while, ever since apparently she got snubbed. 550 00:28:11,240 --> 00:28:13,439 Speaker 1: So, I mean, you make a great point. It certainly 551 00:28:13,440 --> 00:28:16,120 Speaker 1: begs the question he was at that restaurant that night. 552 00:28:16,359 --> 00:28:21,240 Speaker 1: She and Brian Glenn have been trusted people when it 553 00:28:21,240 --> 00:28:24,000 Speaker 1: comes to the administration, trusted by the president. Not many 554 00:28:24,000 --> 00:28:25,760 Speaker 1: people would have known he was going there that night, 555 00:28:25,760 --> 00:28:28,040 Speaker 1: and yet Code Pink showed up, And it just seems 556 00:28:28,119 --> 00:28:31,040 Speaker 1: like there could possibly be a connection to Marjorie Taylor 557 00:28:31,080 --> 00:28:33,560 Speaker 1: Green there. And I certainly hope that she would not 558 00:28:33,800 --> 00:28:37,080 Speaker 1: have risked our national security for a vendetta. But I've 559 00:28:37,080 --> 00:28:39,640 Speaker 1: seen behavior out of her that I just have not 560 00:28:39,760 --> 00:28:42,760 Speaker 1: been able to comprehend and not understand. And I was 561 00:28:42,800 --> 00:28:45,320 Speaker 1: out on the campaign trail with her when we were 562 00:28:45,360 --> 00:28:48,200 Speaker 1: campaigning for Donald Trump, and certainly. 563 00:28:48,040 --> 00:28:49,800 Speaker 2: There was no loss of loyalty there. 564 00:28:49,800 --> 00:28:52,160 Speaker 1: But you brought up the constituents, and I think that's 565 00:28:52,360 --> 00:28:55,520 Speaker 1: what is critical right now as we go into the midterms. 566 00:28:55,760 --> 00:28:59,280 Speaker 1: We have to be able to communicate these manipulations that 567 00:28:59,320 --> 00:29:01,440 Speaker 1: these groups are able to do when it is putting 568 00:29:01,480 --> 00:29:04,600 Speaker 1: money into some of these organizations and they're different in 569 00:29:04,640 --> 00:29:06,959 Speaker 1: no matter what state you're in, that they are on 570 00:29:07,080 --> 00:29:10,880 Speaker 1: the ground trying to manipulate our constituents to get them 571 00:29:10,880 --> 00:29:14,520 Speaker 1: to vote a different way, and they're using our money 572 00:29:14,720 --> 00:29:19,240 Speaker 1: against us with radical propagandas and propaganda and lies. 573 00:29:21,080 --> 00:29:23,320 Speaker 4: Yeah, that's the thing that's so upsetting to me is 574 00:29:23,360 --> 00:29:25,560 Speaker 4: that they're you you know, these big groups and Nevill 575 00:29:25,640 --> 00:29:28,680 Speaker 4: Royce sing I mean, Turlo got close to one of 576 00:29:28,680 --> 00:29:31,000 Speaker 4: the groups that he's a funder of, got close to 577 00:29:31,040 --> 00:29:34,760 Speaker 4: fifty million dollars in taxpayer money. And so the the 578 00:29:35,160 --> 00:29:38,480 Speaker 4: left has gotten so effective as at like taking a 579 00:29:38,520 --> 00:29:41,640 Speaker 4: small chunk of private cash from people like Nevill roy 580 00:29:41,680 --> 00:29:45,760 Speaker 4: Singham or Soros or Gates or whoever, and then augmenting 581 00:29:45,800 --> 00:29:49,120 Speaker 4: that with a massive amount of taxpayer money. And our 582 00:29:49,120 --> 00:29:51,720 Speaker 4: government spends so much money that is so hard for 583 00:29:51,840 --> 00:29:53,760 Speaker 4: I mean, it's a full time job for us and 584 00:29:53,800 --> 00:29:56,680 Speaker 4: a team of fifteen people and you still can't track 585 00:29:56,760 --> 00:29:59,200 Speaker 4: it all. And there's so many others who are also 586 00:29:59,280 --> 00:30:01,200 Speaker 4: doing this kind of work. So there's just so much 587 00:30:01,240 --> 00:30:05,080 Speaker 4: money flowing out that it's like they billions of dollars 588 00:30:05,200 --> 00:30:09,600 Speaker 4: are going into left wing causes, and the same cannot 589 00:30:09,600 --> 00:30:12,280 Speaker 4: be said of the right wing. I mean, there's no 590 00:30:12,400 --> 00:30:16,280 Speaker 4: groups on the right that are using taxpayer money as 591 00:30:16,320 --> 00:30:17,880 Speaker 4: like get out the vote efforts. 592 00:30:18,040 --> 00:30:20,760 Speaker 1: Let's take a quick commercial break. We'll continue next on 593 00:30:20,840 --> 00:30:30,400 Speaker 1: the Tutor Dixon Podcast. So we don't necessarily know this 594 00:30:30,520 --> 00:30:33,320 Speaker 1: unless we have you on and you are putting these 595 00:30:33,400 --> 00:30:35,680 Speaker 1: notes out there all the time. So you're the director 596 00:30:35,720 --> 00:30:38,680 Speaker 1: of research at the Government Accountability Institute. 597 00:30:38,800 --> 00:30:39,920 Speaker 2: Tell people how they. 598 00:30:39,840 --> 00:30:42,600 Speaker 1: Can follow this stuff so that they can learn and 599 00:30:42,640 --> 00:30:44,600 Speaker 1: they can be smart and they can talk to their 600 00:30:44,640 --> 00:30:45,480 Speaker 1: neighbors about it. 601 00:30:46,600 --> 00:30:47,680 Speaker 3: Well, thank you so much, Tutor. 602 00:30:48,000 --> 00:30:52,280 Speaker 4: I am at Seamus Brunner on all platforms, mostly on Twitter, 603 00:30:52,880 --> 00:30:57,600 Speaker 4: Seamus's Sea m us b r u n Er. My 604 00:30:57,680 --> 00:31:01,200 Speaker 4: colleague Peter Schweitzer, He's at Peter Schwitz and we publish 605 00:31:01,240 --> 00:31:05,520 Speaker 4: all of the receipts and investigations at the drilldown dot com. 606 00:31:05,840 --> 00:31:10,040 Speaker 4: That's the drilldown dot com. That's where Schweizer hosts his 607 00:31:10,160 --> 00:31:11,200 Speaker 4: podcast as well. 608 00:31:11,680 --> 00:31:11,840 Speaker 3: Well. 609 00:31:11,880 --> 00:31:14,600 Speaker 2: Thank you so much, Seamus Bruner, thank you for being. 610 00:31:14,400 --> 00:31:17,400 Speaker 1: Here today, Thanks Tutor, and thank you all for joining 611 00:31:17,520 --> 00:31:20,000 Speaker 1: us on the Tutor Dixon Podcast. As always, you can 612 00:31:20,000 --> 00:31:22,960 Speaker 1: find us on the iHeartRadio app, Apple Podcasts or wherever 613 00:31:23,000 --> 00:31:25,120 Speaker 1: you get your podcasts, and you can watch the full 614 00:31:25,200 --> 00:31:28,520 Speaker 1: video on Rumble or YouTube at Tutor Dixon Join us 615 00:31:28,600 --> 00:31:31,200 Speaker 1: next time and have a blasted day.